2025-09-25 –, Apollo
Governing generative AI systems presents unique challenges, particularly for teams dealing with diverse GenAI subdomains and rapidly changing technological landscapes. In this talk, Maarten de Ruiter, Data Scientist at Xomnia, shares practical insights drawn from real-world GenAI use-cases. He will highlight essential governance patterns, address common pitfalls, and provide actionable strategies for teams utilizing both open-source tools and commercial solutions. Attendees will gain concrete recommendations that work in practice, informed by successes (and failures!) across multiple industries
This session offers a practical guide to GenAI governance for teams building with modern data tooling and managing complex, unstructured data pipelines. Drawing from Xomnia’s experience across various GenAI subdomains, Maarten will discuss:
Frameworks for structuring governance across core GenAI use cases, such as LLM integration, data pipelines, prompt management, and monitoring.
- A candid look at tool selection: comparing open-source options and commercial solutions, with suggestions for effective combinations that suit real-world needs.
- Techniques for managing unstructured data quality and AI risk, illustrated with code examples, architecture diagrams, and implementation tips.
- Application of the “GenAI Governance Maturity Matrix” to assess and elevate your team’s practices, with field-tested recommendations drawn from real client use cases.
Expect examples of both what has worked well and what hasn’t, plus the actionable takeaways we wish we’d had from the start. Bring your GenAI governance questions and headaches; the session includes time for troubleshooting and sharing of practical solutions.
Maarten de Ruiter is a Data Scientist at Xomnia, specializing in developing and deploying GenAI applications, most recently focusing on practical governance tools. With a background in Econometrics and Philosophy, he brings both technical expertise and a critical, inquisitive mindset to his work. Maarten has delivered AI-driven solutions across healthcare, logistics, and telecom sectors, and is active in the AI Ethics community. He has contributed to several initiatives and co-authored the paper, 'The AI Ethics Maturity Model: A Holistic Approach to Advancing Ethical Data Science in Organizations.' Outside of work, Maarten enjoys reading, cooking, and exploring Europe by road bike.